Pierre Duhem’s good sense as a guide to theory choice

This paper examines Duhem’s concept of good sense as an attempt to support a non rule-governed account of rationality in theory choice. Faced with the underdetermination of theory by evidence thesis and the continuity thesis, Duhem tried to account for the ability of scientists to choose theories that continuously grow to a natural classification. I will examine the concept of good sense and the problems that stem from it. I will also present a recent attempt by David Stump to link good sense to virtue epistemology. I will argue that even though this approach can be useful for the better comprehension of the concept of good sense, there are some substantial differences between virtue epistemologists and Duhem. In the light of this reconstruction of good sense, I will propose a possible way to interpret the concept of good sense, which overcomes the noted problems and fits better with Duhem’s views on scientific method and motivation in developing the concept of good sense.     

The value of good Biozzi antibody-producing strains of mice for the production of monoclonal antibodies]

We report here that using Biozzi's high and low responder strains of Mice in the preparation of monoclonal antibodies against human T lymphocytes, we observed with the high responder strain 1) a higher number of hybrids; 2) a huge increase in the proportion of hybrids secreting on antibody directed against human lymphocytes.     

Successful visual epistemic representation

In this paper, I characterize visual epistemic representations as concrete two- or three-dimensional tools for conveying information about aspects of their target systems or phenomena of interest. I outline two features of successful visual epistemic representation: that the vehicle of representation contain sufficiently accurate information about the phenomenon of interest for the user's purpose, and that it convey this information to the user in a manner that makes it readily available to her. I argue that actual epistemic representation may involve tradeoffs between these features and is successful to the extent that they are present.     

Integrating mechanistic explanations through epistemic perspectives

Talk of levels is ubiquitous in philosophy, especially in the context of mechanistic explanations spanning multiple levels. The mechanistic conception of levels, however, does not allow for the kind of integration needed to construct such multi-level mechanistic explanations integrating observations from different scientific domains. To address the issues arising in this context, I build on a certain perspectival aspect inherent in the mechanistic view. Rather than focusing on compositionally related levels of mechanisms, I suggest analyzing the situation in terms of epistemic perspectives researchers take when making scientific observations. Characterizing epistemic perspectives along five dimensions allows for a systematic analysis of the relations the scientific observations made from these different epistemic perspectives. This, in turn, provides a solid foundation for integrating the mechanistic explanations that are based on the scientific observations in question.     

Knowing what would happen: The epistemic strategies in Galileo's thought experiments

While philosophers have subjected Galileo's classic thought experiments to critical analysis, they have tended to largely ignored the historical and intellectual context in which they were deployed, and the specific role they played in Galileo's overall vision of science. In this paper I investigate Galileo's use of thought experiments, by focusing on the epistemic and rhetorical strategies that he employed in attempting to answer the question of how one can know what would happen in an imaginary scenario. Here I argue we can find three different answers to this question in Galileo later dialogues, which reflect the changing meanings of ‘experience’ and ‘knowledge’ (scientia) in the early modern period. Once we recognise that Galileo's thought experiments sometimes drew on the power of memory and the explicit appeal to ‘common experience’, while at other times, they took the form of demonstrative arguments intended to have the status of necessary truths; and on still other occasions, they were extrapolations, or probable guesses, drawn from a carefully planned series of controlled experiments, it becomes evident that no single account of the epistemological relationship between thought experiment, experience and experiment can adequately capture the epistemic variety we find Galileo's use of imaginary scenarios. To this extent, we cannot neatly classify Galileo's use of thought experiments as either ‘medieval’ or ‘early modern’, but we should see them as indicative of the complex epistemological transformations of the early seventeenth century.     

Inevitability,contingency, and epistemic humility

This paper offers an epistemological framework for the debate about whether the results of scientific enquiry are inevitable or contingent. I argue in Sections 2 and 3 that inevitabilist stances are doubly guilty of epistemic hubris—a lack of epistemic humility—and that the real question concerns the scope and strength of our contingentism. The latter stages of the paper—Sections 4 and 5—address some epistemological and historiographical worries and sketch some examples of deep contingencies to guide further debate. I conclude by affirming that the concept of epistemic humility can usefully inform critical reflection on the contingency of the sciences and the practice of history of science.     

Scepticism,relativism, and the structure of epistemic frameworks

This paper has four aims: first, to outline the role of the sceptical problem of the criterion in the principal argument for epistemic relativism; second, to establish that methodist and particularist responses to the problem of the criterion do not, by themselves, constitute successful strategies for resisting epistemic relativism; third, to argue that a more fruitful strategy is to attempt to evaluate epistemic frameworks on the basis of the epistemic resources that they have in common; and finally, to make the case that finding this common ground will necessarily involve determining how it is that a framework’s constituent epistemic methods depend on one another for not only their warrant, but for their application.     

Prediction in context: On the comparative epistemic merit of predictive success

The considerations set out in the paper are intended to suggest that in practical contexts predictive power does not play the outstanding roles sometimes accredited to it in an epistemic framework. Rather, predictive power is part of a network of other merits and achievements. Predictive power needs to be judged differently according to the specific conditions that apply. First, predictions need to be part of an explanatory framework if they are supposed to guide actions reliably. Second, in scientific expertise, the demand for accurate predictions is replaced with the objective of specifying a robust corridor of estimates. Finally, it is highly uncertain to predict the success of research projects. The overall purpose of the paper is to enlarge the debate about predictions by addressing specifically the roles of predictions in application-oriented research.     

Making sense of non-factual disagreement in science

Philosophical discussions of disagreement typically focus on cases in which the disagreeing agents are aware that they are disagreeing and can pinpoint the proposition that they are disagreeing about. Scientific disagreements are not, in general, like this. Here we consider several case studies of disagreements that do not concern first-order factual claims about the scientific domain in question, but rather boil down to disputes regarding methodology. In such cases, it is often difficult to identify the point of contention in the dispute. Philosophers of science have a useful role to play in pinpointing the source of such disagreements, but must resist the temptation to trace scientific debates to disputes over higher-level philosophical accounts.     

Crustal layering, simplicity, and the oil industry: The alteration of an epistemic paradigm by a commercial environment

This paper proposes that the gradual alteration of the predominant epistemic paradigm in crustal seismology in the interwar period—namely, simplicity—came about because of the strong influence of a particular commercial environment, i.e. the oil industry. I begin by demonstrating the interwar predominance of Jeffreys’ ‘simplicity postulate’ and his probabilistic epistemology, highlighting the espousal by several seismologists (Bullen, Stoneley, Byerly), whose crustal models drew on mathematical idealisations. Next, I demonstrate that the renunciation of simplicity in the 1930s came about too quickly, and, above all, too heterodoxically to have been the result of new geological evidence. Rather, I argue, the paradigm shift among seismologists was a result of the significant rise in seismic exploration generated by the oil industry. Driven by market demands, American petroleum companies pioneered new technologies, organised research initiatives, and trained young geophysicists who, through the fusion of experimentalism and field experience, brought about fundamental progress in earthquake seismology. Remarkably, historians of science have almost entirely failed to recognise the interwar primacy of the simplicity paradigm as well as its subsequent renunciation. More importantly, they have failed to acknowledge the role the oil industry played in contributing to this renunciation and to the development of new paradigms in seismology.     

Data,epistemic values,and multiple methods in case study research

Case Study research is characterized by the employment of multiple data gathering methods. In this paper, I examine the concurrent use of participant observation and qualitative interviews. The question I examine is: what is the rationale behind their combination in case study research? In the literature on case study research, the two most common reasons for using multiple methods appeal to comprehensiveness and convergent confirmation respectively. I argue that there is a third significant, yet overlooked, way to motivate the joint use of participant observation and qualitative interviews: the methods may generate complementary evidence and this puts the researcher in a better position to confirm that her data manifest central epistemic values and so are suitable as a basis for providing an adequate answer to her research question. I refer to this as the rationale of “blended epistemic value validation”.     

Forecasting aggregate market volatility: The role of good and bad uncertainties

We decompose economic uncertainty into "good" and "bad" components according to the sign of innovations. Our results indicate that bad uncertainty provides stronger predictive content regarding future market volatility than good uncertainty. The asymmetric models with good and bad uncertainties forecast market volatility in a better way than the symmetric models with overall uncertainty. The combination for asymmetric uncertainty models significantly outperforms the benchmark of autoregression, as well as the combination for symmetric models. The revealed volatility predictability is further demonstrated to be economically significant in the framework of portfolio allocation.